Course Syllabus

Overview

Students should watch Canvas/Ed Lessons course videos according to the following schedule. It is recommended for students to do lab sessions on the schedule by yourself as early as possible since some of homework may cover the lab materials scheduled later than the homework. For the online video lectures, CS/CSE students should go to Udacity or Canvas to access to the sources.

Schedule

Week #DatesVideo lessonsLabDeliverable & Due (EDT)
1Aug 22-26[1. Intro to Big Data Analytics], [2. Course Overview]
2Aug 29- Sep 2[3. Predictive Modeling][Hadoop & HDFS Basics]HW1 Due (Sep 5)
3Sep 5-9[4.MapReduce]& [HBase][Hadoop Pig & Hive]
4Sep 12-16[5.Classification evaluation metrics], [6.Classification ensemble methods]HW2 Due (Sep 19)
5Sep 19-23[7. Phenotyping], [8. Clustering][Scala Basic], [Spark Basic], [Spark SQL]
6Sep 26-30[9. Spark][Spark Application] & [Spark MLlib]HW3 Due & Project Group Formation (Oct 3)
7Oct 3-7[10. Medical ontology][NLP Lab]
8Oct 10-14[11. Graph analysis][Spark GraphX]Project Proposal Due (Oct 17)
9Oct 17-21[12. Dimensionality Reduction], [13. Patient similairty], [14. CNN][Deep Learning Lab]HW4 Due (Oct 24)
10Oct 24-28[15. DNN], [16. RNN]
11Oct 31- Nov 4Project DiscussionHW5 Due (Nov 7)
12Nov 7-11Project Discussion
13Nov 14-18Project DiscussionProject Draft Due (Nov 21)
14Nov 21-25Project DiscussionFinal Exam (Nov 27-28)
15Nov 28-Dec 2Project DiscussionFinal Project Due (Dec 5)
16Dec 5-9Project Submission

Previous Guest Lectures

See RESOURCE section.